Apprentice Engineer - Artificial Intelligence / Machine Learning

Apprentice Engineer – Artificial Intelligence / Machine Learning
Mountain View, CA

This role is not eligible for visa sponsorship. Applicants must be authorized to work in the US for LinkedIn without requiring visa sponsorship now or in the future.

To learn more about the program and the application questions and timeline, please visit: careers.linkedin.com/reach.

Company Description
LinkedIn is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed. Join us to transform the way the world works.

Searching for your dream job? At LinkedIn, we have developed an apprenticeship program that creates opportunity for every individual with the passion, potential, and drive to either develop or restart their career in engineering. We fundamentally believe top talent can come from anywhere, regardless of educational training or professional experience.

REACH Program
REACH is a multi-year program where individuals with passion for engineering will work in technical roles to build their skill set and gain the experience needed to become an Engineer at LinkedIn. The time each apprentice spends in this program will vary depending on their incoming skill set, experience, and progress through the program. The time in program is a one year minimum and a five year maximum in the apprenticeship. This program is designed for candidates who have non-traditional career paths and we strongly encourage those candidates to apply. This includes but is not limited to: candidates without Computer Science degrees who are self-taught, those that are re-entering the workforce, individuals switching careers, or those who have attended boot camp style courses focusing on machine learning or data science.

Hybrid Work
At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can both work from home and commute to a LinkedIn office, depending on what’s best for you and when it is important for your team to be together.
Artificial Intelligence/ Machine Learning Apprenticeship
As an Apprentice Engineer, you will be placed on an Artificial Intelligence/ Machine Learning engineering team at LinkedIn developing cutting-edge machine learning models that serve millions of members. You will learn from fellow engineers and leaders and develop key skills applicable to a career in Artificial Intelligence/Machine Learning. Furthermore, apprentices are guaranteed a percentage of time to focus on their personal technical development, using both LinkedIn’s internal ecosystem and external educational opportunities.

Is Artificial Intelligence/ Machine Learning a good fit for me?
You might be a good fit for this apprentice role if you have strong quantitative
and problem-solving skills, regardless of the areas in which you developed them or applied them. There are endless possibilities for the experiences that have prepared you for this apprenticeship. For example, you might be someone working in analytics or software engineering who has been wanting to switch to artificial intelligence/ machine learning. You might be someone with a background in social science who has applied quantitative methods in that arena. You might be someone whose hobby is thinking about improvements to sports statistics like expected goals, home runs, or team rankings.

Job Responsibilities:
• Contribute a unique perspective and creative approach to solving problems at LinkedIn
• Continue to learn and develop artificial intelligence/ machine learning skills
• Under the mentorship and guidance of seasoned LinkedIn engineers, produce high-quality software that is tested, code reviewed, and checked in regularly for continuous integration
• Solve difficult problems with machine learning, write code to put those solutions into production or inform business decision making, and deliver with a sense of urgency and quality
• Develop machine learning models that will serve our 740 million members on LinkedIn

Basic Qualifications: 
• An undergraduate or graduate degree (bachelor’s, master’s or doctorate) in any field
• Demonstrated history of independent problem solving, data-driven thinking, and quantitative skills. These skills may have been gained or demonstrated as part of a degree program or prior work experience. These do not have to be in a technology setting, but rather any situation in which you used math and code to help drive decisions or outcomes.
• Demonstrated history of Artificial Intelligence/Machine Learning related projects. There is a wide range of examples that will qualify, including but not limited to:
● Open-source contributions
● Personal analytics or machine learning projects
● Analytical, mathematical, or statistical work as part of a job or research

Preferred Qualifications: 
• Understanding of CS basic concepts: variables, recursion, algorithms, data structures, object orientation, error handling, etc. Knowing these will make it easier for you to learn more complex software topics!
• Basic knowledge of common machine learning techniques such as regression, clustering, and tree-based methods
• Excellent collaborative and communication skills, and ability to clearly articulate your perspective
• Entrepreneurial mindset to bring in a new and unique perspective to the team
• Desire to learn and develop skills in the fields of artificial intelligence/ machine learning

Suggested Skills:
•Statistics & Machine Learning concepts and algorithms
•Data Analysis
•Experience with coding in programming/scripting languages such as Python, R, Java, C++, Matlab, SQL

LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $80,000 to $107,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor.

The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits.

 
Application Requirements:
Our application process is designed to give individuals the opportunity to show us a range of qualities we believe will make them successful engineers. This includes their drive and ability to learn, tenacity and work ethic, unique perspective and passion for engineering. As part of the application process, individuals are required to submit responses to the application questions and responses will be reviewed for completeness as well as content. To review the questions, including recommended length for each, please visit the role description at careers.linkedin.com/reach.

Please note, resumes and LinkedIn profiles will NOT be considered as part of the evaluation for REACH. Therefore, please make sure that any information you would like us to know is highlighted in your application responses.

Equal Opportunity Statement
LinkedIn is committed to diversity in its workforce and is proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is an Affirmative Action and Equal Opportunity Employer as described in our equal opportunity statement here: https://lnkd.in/equalemploymentopportunity2017. Please reference http://www1.eeoc.gov/employers/upload/eeoc_self_print_poster.pdf and https://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf for more information.
LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.

If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation.

Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:

-Documents in alternate formats or read aloud to you
-Having interviews in an accessible location
-Being accompanied by a service dog
-Having a sign language interpreter present for the interview

A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.

LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.
Pay Transparency Policy Statement
As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.
Global Data Privacy Notice for Job Candidates
This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://lnkd.in/GlobalDataPrivacyNotice